Zach Stagers

Are you ready to take your Spark skills to the next level? This one-day, hands-on workshop is designed for data engineers who want to master advanced Spark techniques and build scalable, high-performance solutions.

Sharing code effectively is key to building scalable and maintainable data solutions. Whether you're deploying Python libraries or moving workflows across environments, efficient code distribution ensures consistency, reduces errors, and streamlines collaboration.

The lakehouse design paradigm is becoming more mainstream as tools like Azure Synapse and Databricks make querying lake-based data simple, but bring a huge amount of power. But there is yet to emerge a defacto industry standard in serving a lake-based model to end users, and with a growing number of options it can be difficult make a decision that best fits your scenario. In this session we will establish a benchmark of what we're looking for in a good data serving layer. We will then review the serving options currently available to evaluate how well they meet our requirements, any additional benefits and some potential pitfalls and things to avoid with each. You will leave the session equipped with everything you need to open up your lake to the wider business and harness the power of the lakehouse model.

Azure Synapse Analytics has been steadily maturing and growing since it's release, but it's still hard to know where to start! This introductory training session will give you a grounding in all of the Synapse engines so you'll know your Spark Pool from your SQL Pools and be ready to hit the...